惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

B
Blog
V
Vulnerabilities – Threatpost
Apple Machine Learning Research
Apple Machine Learning Research
V
V2EX
博客园 - 叶小钗
阮一峰的网络日志
阮一峰的网络日志
人人都是产品经理
人人都是产品经理
Latest news
Latest news
博客园 - 三生石上(FineUI控件)
美团技术团队
aimingoo的专栏
aimingoo的专栏
Google Online Security Blog
Google Online Security Blog
Security Archives - TechRepublic
Security Archives - TechRepublic
T
Threatpost
Y
Y Combinator Blog
T
Tailwind CSS Blog
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
A
Arctic Wolf
C
Cyber Attacks, Cyber Crime and Cyber Security
小众软件
小众软件
Recent Commits to openclaw:main
Recent Commits to openclaw:main
T
Tenable Blog
W
WeLiveSecurity
L
LINUX DO - 热门话题
D
Docker
Cyberwarzone
Cyberwarzone
量子位
A
About on SuperTechFans
The Last Watchdog
The Last Watchdog
雷峰网
雷峰网
C
CERT Recently Published Vulnerability Notes
P
Palo Alto Networks Blog
The Hacker News
The Hacker News
Blog — PlanetScale
Blog — PlanetScale
P
Proofpoint News Feed
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
F
Full Disclosure
The Cloudflare Blog
T
The Blog of Author Tim Ferriss
T
The Exploit Database - CXSecurity.com
Engineering at Meta
Engineering at Meta
O
OpenAI News
Hacker News - Newest:
Hacker News - Newest: "LLM"
Scott Helme
Scott Helme
IT之家
IT之家
S
Secure Thoughts
MongoDB | Blog
MongoDB | Blog
L
Lohrmann on Cybersecurity
博客园 - 司徒正美
Google DeepMind News
Google DeepMind News

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant Common SOC 2 Failures (Real World) Stop Vibe-Checking Your AI App: A Practical Guide to Evals How to Use SonarQube and SonarScanner Locally to Level Up Your Code Quality Your Next To-Do App Is Dead — I Replaced Mine with an OpenClaw AI Sign a Nostr event in 60 lines of Python using coincurve — no nostr-sdk, no nbxplorer, no rust toolchain ITGC Audit Explained Like You’re in Big 4 Patch Tuesday abril 2026: Microsoft parcha 163 vulnerabilidades y un zero-day en SharePoint Stop scraping everything: a better way to track competitor price changes Listing on MCPize + the Official MCP Registry while routing payments OUTSIDE the marketplace — how I kept 100% of my x402 revenue Building an AI-Powered Risk Intelligence System Using Serverless Architecture Why We Ripped Function Overloading Out of Our AI Toolchain Testing AI-Generated Code: How to Actually Know If It Works SaaS Churn Is Killing Your Business. Here Is What to Do About It (Without a Support Team) The Speed of AI Is No Longer Linear - And Self-Improving Models Are Why How to Implement RBAC for MCP Tools: A Practical Guide for Engineering Teams From Standard Quote to Persuasive Proposal: AI Automation for Arborists I built a CLI that scaffolds complete multi-tenant SaaS apps Axios CVE-2025–62718: The Silent SSRF Bug That Could Be Hiding in Your Node.js App Right Now The dashboard that ended our friendship Data Pipelines Explained Simply (and How to Build Them with Python) The Hidden Cost of AI Systems Nobody Talks About. undefined vs undeclared, and how typeof behaves Switching from file-based jobs to NATS/Kafka in Rust without changing code io_uring Adventures: Rust Servers That Love Syscalls Why Agentic AI is Killing the Traditional Database The POUR principles of web accessibility for developers and designers Quantum Neural Network 3D — A Deep Dive into Interactive WebGL Visualization How To Install Caveman In Codex On macOS And Windows Automation Pipeline Reliability: Why Your Workflow Breaks When Nobody Is Watching I Built an 'Open World' AI Coding Agent — It Works From ANY Folder From Freelancing to Product: A Tech Service Company's SaaS Transformation China's AI Giants: Adding Tencent Hunyuan & ByteDance Doubao to AI University (74 Providers) On the Vibe Coders and Their Lies clerk: Auto-Summarize Your Claude Code Sessions AI Weekly — 2026/04/10–04/17 | The Model Lockdown Is Here, but the Toolchain Is the Real Battleground AI 週報 — 2026/04/10–2026/04/17 模型封鎖潮來了,但工具鏈才是真戰場 Maybe this is how Open-Source apps are born... 🚀 Fine-Tune LLMs with LoRA and QLoRA: 2026 Guide tRPC v11 + Next.js App Router: End-to-End Type Safety Without the Boilerplate ShadCN UI in 2026: Why I Stopped Installing Component Libraries and Started Owning My Components SaaS Billing in React Server Components: Stripe + Supabase Without a Single `useEffect` Join our DEV Weekend Challenge — $1,000 in Prizes Across TEN winners! Submissions Due April 20 at 6:59 AM UTC. Implementing FSRS Spaced Repetition in Flutter + Supabase — Adding Memory Science to an AI Learning App "I Texted My Localhost From the Train — Claude Code Fixed the Bug Before I Got Home" I Built a Sales Prep AI and It Went Deeper Than Expected Design to Code #2: One JSON, Eleven Outputs Solving the 100M-Row Problem: A Summary Table Pattern for High-Volume Push Notification Logs Flutter Web With Wasm: What Actually Changes For Developers I Built 50 Royalty-Free Soundtracks for My Side Project in a Weekend Using AI Music Generation The Vibe Coding Security Checklist: 7 Things to Check Before You Ship Stop Letting Googlebot Guess Fix Your React App's SEO Right Desconstruindo o Streaming do LinkedIn: Como Criar um Engine de Extração de Vídeo de Alta Performance com HLS e FFmpeg (EDA Part-1) EDA (Exploratory Data Analysis) Explained With Real Life — Why Looking at Your Data Is the Most Important Step in Machine Learning Brand Relationship Management at Scale: Our 4-Touch Outreach System for 200+ Brands Why String.fromEnvironment() Might Return an Empty String in Dart JGuardrails 1.0.0 — Hardening Java LLM Apps Against Jailbreaks, Toxicity, and Prompt Injection Plan and Schedule a Full Week of Threads Content From One Claude Conversation Coding Cat Oran Ep3, Five Tables Changed Everything Updated: BFF Pattern I'm done watching freelancers get buried by 200 proposals. So I'm building the alternative. This is my first post BFS Algorithm in Java Step by Step Tutorial with Examples Tracking LLM Pricing Monthly: An Open Dataset for 22 AI Models How We Measure Content ROI on a Comparison Site: Revenue Attribution Without Perfect Data Introducing Nova AI Ops: The AI-Native Operating System for SRE Teams I built a free desktop video downloader for Windows — Grabbit How Talkie OCR Helps Vision-Impaired & Dyslexic Users Read the World Around Them VRCFaceTracking安装和iPhone面捕配置教程,有bug Even CrowdStrike Can't See Your Agents The Automation Gold Rush: What n8n Workflows and Claude Are Opening Up for Developers Right Now
FastAPI doesn't speak your users' language. Here's how to fix that.
Radomir Brkovic · 2026-06-25 · via DEV Community

Most FastAPI tutorials end at "it works in English." But the moment you ship to users in Germany, Brazil, or Japan, you realize FastAPI has no built-in answer for internationalization — not in models, not in validation errors, not in API responses.

This post shows exactly how FastKit Core solves i18n end-to-end: translatable database fields, translated validation errors, and a standardized response format that frontend teams actually love working with.


The problem in concrete terms

Let's say you're building a product catalog for a multinational SaaS. You need article titles in English, German, and French. Here's what you'd normally do in FastAPI:

# The "usual" approach — store as JSON manually
class Article(Base):
    __tablename__ = "articles"
    id: Mapped[int] = mapped_column(primary_key=True)
    title: "Mapped[dict] = mapped_column(JSON)  # {\"en\": \"...\", \"de\": \"...\", \"fr\": \"...\"}"

# Then manually handle locale everywhere
article = session.get(Article, 1)
locale = request.headers.get("Accept-Language", "en")[:2]
title = article.title.get(locale) or article.title.get("en")  # manual fallback

And then in every validation error response, you return Pydantic's default English-only messages. And then your frontend has to parse inconsistent JSON shapes across endpoints.

Three separate problems — all unsolved by FastAPI out of the box.


Solution 1: TranslatableMixin — i18n directly in your SQLAlchemy model

FastKit Core ships a TranslatableMixin that makes multi-language fields completely transparent. You declare which fields are translatable, and from then on they behave like normal strings — reading and writing the current locale automatically.

from sqlalchemy import JSON
from sqlalchemy.orm import Mapped, mapped_column
from fastkit_core.database import Base, BaseWithTimestamps, IntIdMixin, TranslatableMixin

class Article(Base, IntIdMixin, BaseWithTimestamps, TranslatableMixin):
    __translatable__ = ['title', 'content']
    __fallback_locale__ = 'en'

    title: Mapped[dict] = mapped_column(JSON)
    content: Mapped[dict] = mapped_column(JSON)
    author_id: Mapped[int]

That's the entire model. Now here's how you use it:

article = Article()

# Write English
article.title = "How to build scalable APIs"

# Switch to German and write
article.set_locale('de')
article.title = "Wie man skalierbare APIs entwickelt"

# Switch to French
article.set_locale('fr')
article.title = "Comment construire des APIs évolutives"

# Read back — always returns current locale
article.set_locale('en')
print(article.title)  # "How to build scalable APIs"

article.set_locale('de')
print(article.title)  # "Wie man skalierbare APIs entwickelt"

# Get all translations at once
print(article.get_translations('title'))
# {'en': 'How to build scalable APIs', 'de': 'Wie man skalierbare APIs entwickelt', 'fr': 'Comment construire des APIs évolutives'}

What's actually happening under the hood: the mixin overrides __getattribute__ and __setattr__ to intercept reads and writes on translatable fields, storing them in a {"locale": "value"} dict that gets serialized to a JSON column. SQLAlchemy event listeners handle serialization before insert/update and deserialization after load.

The result is transparent — you write article.title = "Hello" and the mixin takes care of the rest.

Locale from request — automatic with LocaleMiddleware

FastKit Core ships a ready-made LocaleMiddleware that you register once and forget. Add it to your app and every request automatically sets the correct locale for both model reads and translation lookups:

from fastapi import FastAPI
from fastkit_core.http import LocaleMiddleware

app = FastAPI()
app.add_middleware(LocaleMiddleware)

That's it. No custom middleware to write, no set_locale() calls scattered through your handlers.

The middleware resolves locale with the following priority:

  1. Accept-Language request header (e.g. de, fr, en)
  2. ?lang= query parameter (e.g. /articles?lang=de)
  3. locale cookie
  4. Default: en This means a German user whose browser sends Accept-Language: de gets German responses automatically. A user who explicitly visits /articles?lang=fr gets French. A returning user with a locale cookie set during login gets their saved preference. All without touching a single route handler.

After this middleware is registered, every TranslatableMixin model in every request automatically reads and writes the correct locale. No passing locale around. No article.title.get(locale) everywhere.

Fallback behavior

If a translation doesn't exist for the requested locale, it falls back to __fallback_locale__ automatically:

article.set_locale('es')  # Spanish not set
print(article.title)  # "How to build scalable APIs" — English fallback


Solution 2: Translated validation errors with _()

FastAPI + Pydantic gives you validation out of the box, but errors always come out in English, with Pydantic's internal message format. If you're serving a German user, they get:

{
  "detail": [
    {
      "loc": ["body", "email"],
      "msg": "value is not a valid email address",
      "type": "value_error.email"
    }
  ]
}

FastKit Core replaces this with a Laravel-style _() helper backed by JSON translation files, and a BaseSchema that formats errors into a clean, consistent structure.

Setting up translation files

translations/
├── en.json
├── de.json
└── fr.json

// translations/en.json
{
  "validation": {
    "required": "The {field} field is required.",
    "string_too_short": "The {field} field must be at least {min_length} characters.",
    "string_too_long": "The {field} field must not exceed {max_length} characters.",
    "email": "The {field} field must be a valid email address.",
    "value_error": "{field} is invalid."
  },
  "messages": {
    "welcome": "Welcome, {name}!",
    "article_created": "Article created successfully."
  }
}

// translations/de.json
{
  "validation": {
    "required": "Das Feld {field} ist erforderlich.",
    "string_too_short": "Das Feld {field} muss mindestens {min_length} Zeichen lang sein.",
    "string_too_long": "Das Feld {field} darf maximal {max_length} Zeichen haben.",
    "email": "Das Feld {field} muss eine gültige E-Mail-Adresse sein.",
    "value_error": "{field} ist ungültig."
  },
  "messages": {
    "welcome": "Willkommen, {name}!",
    "article_created": "Artikel erfolgreich erstellt."
  }
}

Using _() in your code

from fastkit_core.i18n import _, set_locale

set_locale('en')
print(_('messages.welcome', name='Maria'))
# "Welcome, Maria!"

set_locale('de')
print(_('messages.welcome', name='Maria'))
# "Willkommen, Maria!"

The locale context is shared between _() and TranslatableMixin — setting it once via middleware affects both model reads and translation lookups.

BaseSchema — structured, translated validation errors

BaseSchema extends Pydantic's BaseModel with a format_errors() classmethod that maps Pydantic's internal error types to your translation keys and returns a clean dict:

from pydantic import EmailStr
from fastkit_core.validation import BaseSchema

class ArticleCreate(BaseSchema):
    title: str
    email: EmailStr
    content: str

When validation fails, instead of calling exc.errors() and getting Pydantic's raw output, you call format_errors():

from pydantic import ValidationError
from fastkit_core.validation import BaseSchema
from fastkit_core.i18n import set_locale

set_locale('de')

try:
    ArticleCreate(title="", email="not-an-email", content="Hello")
except ValidationError as exc:
    errors = ArticleCreate.format_errors(exc)
    print(errors)

Output (in German):

{
  "email": ["Das Feld email muss eine gültige E-Mail-Adresse sein."],
  "title": ["Das Feld title ist erforderlich."]
}

Same code, different locale set in middleware → different language in errors. No if/else, no per-field translations.


Solution 3: Standardized response format

The third piece of the puzzle is consistent API responses. FastKit Core provides four response helpers that enforce the same JSON envelope across every endpoint:

from fastkit_core.http import success_response, error_response, paginated_response

success_response

@router.get("/{id}")
async def show(id: int, service: ArticleService = Depends(get_service)):
    article = await service.get_or_404(id)
    return success_response(data=article)

{
  "success": true,
  "data": {
    "id": 1,
    "title": "How to build scalable APIs",
    "content": "...",
    "author_id": 42
  }
}

paginated_response

@router.get("")
async def index(page: int = 1, service: ArticleService = Depends(get_service)):
    items, meta = await service.paginate(page=page, per_page=20)
    return paginated_response(items=items, pagination=meta)

{
  "success": true,
  "data": [...],
  "pagination": {
    "page": 1,
    "per_page": 20,
    "total": 143,
    "total_pages": 8,
    "has_next": true,
    "has_prev": false
  }
}

error_response — with translated validation errors

from fastkit_core.http import error_response
from fastkit_core.i18n import _

@router.post("")
async def store(data: ArticleCreate, service: ArticleService = Depends(get_service)):
    try:
        article = await service.create(data)
        return success_response(data=article, status_code=201)
    except ValidationError as exc:
        errors = ArticleCreate.format_errors(exc)
        return error_response(
            message=_('validation.failed'),
            errors=errors,
            status_code=422
        )

{
  "success": false,
  "message": "Validierung fehlgeschlagen.",
  "errors": {
    "title": ["Das Feld title ist erforderlich."],
    "email": ["Das Feld email muss eine gültige E-Mail-Adresse sein."]
  }
}

The frontend team gets success: true/false to branch on, data always at the same key, errors always as { field: [messages] }, and pagination always in the same shape. No defensive parsing, no "what does this endpoint return?" questions.


Putting it all together — a full multilingual endpoint

First, register the middleware once in your main.py:

from fastapi import FastAPI
from fastkit_core.http import LocaleMiddleware

app = FastAPI()
app.add_middleware(LocaleMiddleware)

That's the entire setup. From this point, every request automatically carries the correct locale through your entire stack — models, translations, validation errors, and responses.

The router itself stays completely clean:

from fastapi import APIRouter, Depends
from fastkit_core.database import get_async_db
from fastkit_core.http import success_response, paginated_response
from sqlalchemy.ext.asyncio import AsyncSession
from .service import ArticleService
from .schemas import ArticleCreate, ArticleResponse

router = APIRouter(prefix='/articles', tags=['Articles'])

def get_service(session: AsyncSession = Depends(get_async_db)) -> ArticleService:
    return ArticleService(session)

@router.get("")
async def index(
    page: int = 1,
    service: ArticleService = Depends(get_service)
):
    items, meta = await service.paginate(page=page, per_page=20)
    return paginated_response(items=items, pagination=meta)

@router.get("/{id}")
async def show(id: int, service: ArticleService = Depends(get_service)):
    article = await service.get_or_404(id)
    return success_response(data=article)

@router.post("", status_code=201)
async def store(data: ArticleCreate, service: ArticleService = Depends(get_service)):
    article = await service.create(data)
    return success_response(data=article, status_code=201)

A German user hitting GET /articles with Accept-Language: de gets article titles in German. An English user gets them in English. Validation errors come back in the right language automatically. The response shape is identical either way.


Why this matters beyond convenience

In a multinational SaaS, i18n is not a feature you add later — it's infrastructure. Retrofitting it after the fact means touching every model, every validation schema, every response, and every frontend integration.

FastKit Core makes it a day-one decision with almost no ceremony:

  • One mixin on your model declares which fields are translatable
  • One middleware sets the locale per request
  • One base schema formats errors in the right language
  • Four response helpers standardize every endpoint output The patterns were built from real production experience migrating Laravel applications to FastAPI — where Laravel's i18n and response conventions were things we sorely missed.

Getting started

pip install fastkit-core

Full documentation at fastkit.org/docs — including the TranslationManager API, locale middleware configuration, and how TranslatableMixin works with async sessions.

If this solved a problem you've been working around, a ⭐ on GitHub goes a long way for a small open-source project.